



"""simple docstring"""





# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

import torch

from ..models.auto import AutoModelForVisualQuestionAnswering, AutoProcessor
from ..utils import requires_backends
from .base import PipelineTool


if TYPE_CHECKING:
  from PIL import Image
class  lowercase__  (       SCREAMING_SNAKE_CASE ):







       '''simple docstring'''


       UpperCamelCase		=	'''dandelin/vilt-b32-finetuned-vqa'''
       UpperCamelCase		=	(
           '''This is a tool that answers a question about an image. It takes an input named `image` which should be the '''
           '''image containing the information, as well as a `question` which should be the question in English. It '''
           '''returns a text that is the answer to the question.'''
       )
       UpperCamelCase		=	'''image_qa'''
       UpperCamelCase		=	AutoProcessor
       UpperCamelCase		=	AutoModelForVisualQuestionAnswering

       UpperCamelCase		=	['''image''', '''text''']
       UpperCamelCase		=	['''text''']



       def __init__(				self     :    Dict						,							*_UpperCAmelCase     :    Dict						,							**_UpperCAmelCase     :    Any       )					->		Tuple:


             '''simple docstring'''




             requires_backends(self						,							["vision"]       )
             super().__init__(*_UpperCAmelCase						,							**_UpperCAmelCase       )



       def 	lowercase__							(				self     :    int						,							_UpperCAmelCase     :    "Image"						,							_UpperCAmelCase     :    str       )					->		Optional[int]:


             '''simple docstring'''




             return self.pre_processor(_UpperCAmelCase						,							_UpperCAmelCase						,							return_tensors="pt"       )



       def 	lowercase__							(				self     :    Optional[int]						,							_UpperCAmelCase     :    Any       )					->		Tuple:


             '''simple docstring'''




             with torch.no_grad():
                   return self.model(**_UpperCAmelCase       ).logits







       def 	lowercase__							(				self     :    str						,							_UpperCAmelCase     :    str       )					->		Optional[Any]:


             '''simple docstring'''




             UpperCAmelCase_     					=				outputs.argmax(-1       ).item()
             return self.model.config.idalabel[idx]





def 				lowerCAmelCase__       (			a__    ,     a__    ,     a__    ,     a__    ,     a__ )      ->int:




  '''simple docstring'''

  if index == number_of_items:
    return 0
  _UpperCamelCase           =    0
  _UpperCamelCase           =    0
  _UpperCamelCase           =    knapsack(a__    ,     a__    ,     a__    ,     a__    ,     index + 1 )
  if weights[index] <= max_weight:
    _UpperCamelCase           =    values[index] + knapsack(
        a__    ,     a__    ,     a__    ,     max_weight - weights[index]    ,     index + 1 )
  return max(a__    ,     a__ )


if __name__ == "__main__":
   import doctest

   doctest.testmod()




